Login AI
AI automation of business processes
We set up AI automation of business processes for operations teams. We build the process map, add routing and data extraction, and set up approvals, retries, and monitoring. The base covers 3 processes and 2 integrations; the pilot takes 3–4 weeks.
We place AI steps into approvals, routing, and documents: a request travels from trigger to system write, and you see the status of every run.
Pricing
from ₽600,000
per project
This is the lower bound of a project. We scope the exact quote after a brief: it depends on volume and the number of integrations.
Capabilities
A process map and three automations
We break the process into steps, count manual work in hours, and build three automations: approvals, routing, and documents.
AI routing and data extraction
The model identifies the request type, selects a queue, and extracts fields from an email, invoice, or contract. The process owner sets the rules.
Approvals with a decision log
Every human step gets a deadline, a role, and a log entry: who approved and when. An overdue approval moves on through escalation.
Monitoring, retries, and alerts
On failure the node retries with a delay and writes the event to the log, and the on-call engineer gets an alert. The panel shows the share of successful operations.
From request to result
1
Process audit
We walk the process with the owner and the operators, record the steps, the time for each, and the systems. You get a map with manual work measured in hours.
2
Workflow design
We draw the data route: trigger, checks, AI step, approval, system write. For each step we fix the input, output, deadline, and action on failure.
3
Build and integrations
We build the scenario in n8n or Make, connect CRM, ERP, email, and documents through APIs. We set up access, a test environment, and a run on a data copy.
4
Pilot and monitoring
We run it on the real flow for 3–4 weeks, compare the result with manual work, and adjust the rules with the owner. We turn on retries and alerts.
Check if it fits you
Good fit
Repeating processes with APIs
Requests, invoices, approvals, and notifications already live in systems with APIs. The scenario reads the data, sends it through an AI step, and writes the result to CRM.
An owner for the process
A business-side person sets the routing conditions, approves changes, and resolves disputed cases. The process gets an owner, and the scenario gets clear rules.
Not a fit
Processes without APIs or data
When the input sits on paper or in a locked file, collection and digitization come first. Automation starts once the data reaches a system.
Hard real-time requirements
A response in milliseconds and custom logic need a separate backend. A low-code platform works at scenario steps and suits flows with delays in seconds.
What you get
−60%
time to prepare material
In the agency-content-pipeline project the pipeline prepared material from briefs, an editor and a tone check approved the copy, and publication followed the calendar. Publishing volume grew threefold.
3
Three processes in the base
The base package includes three processes: approvals, routing, and documents. Each gets a map, a test environment, and monitoring.
2
Two integrations in the base
The base package includes two integrations: CRM and document storage. We connect extra systems through APIs and price them separately.
100%
Actions in the log
We write every scenario action to the log: the process owner sees the input, step, and result, so review rests on records and exact data.
What the delivery includes
A process map
A process map shows every step, the systems at the input and output, approval deadlines, and the points where a person works.
Three automations
We build three automations in n8n or Make, connect them to your systems, and hand them over with a guide to changing rules.
Monitoring and a report
Monitoring and a report give you a panel with run counts, the share of successful operations, and an error list for the period.
How the system is built
A trigger starts the run
The scenario starts from a CRM webhook, a new email, or a schedule, takes the input data, and passes it to the next step, so processing begins at the moment of the event.
The AI step
The AI step classifies the request, extracts fields from an email or invoice, and prepares a reply draft under team rules. The next step receives data and an action.
Approval and log
An approval gets a deadline, a role, and a log entry, and a repeated node run checks the status and continues the route from the stopping point. The decision history stays complete.
Where the solution pushes back
- 01
Low-code limits
We move complex logic into a separate service and call it from the scenario, so heavy computation and proprietary models live outside low-code.
- 02
The process owner's role
Routing rules change with the process, so the process owner approves changes and resolves disputed cases. We hand over the rule reference.
- 03
Monitoring and support
Monitoring needs an on-call person who reviews errors and decides on escalation. We set the alert levels and hand over the support policy.
Technologies
The technologies we use in our work and their role in a project.
Platforms and infrastructure
We build scenarios on n8n or Make. The event queue runs in Kafka, run state lives in PostgreSQL, and Redis gives fast access to intermediate data.
Cost calculator
This is an indicative range, not a quote. We scope the exact estimate after a brief: it depends on volume and the number of integrations.
Processes
Integrations
Operation volume
Add-ons
Support
Year one: updates and monitoring, a reply within 2 business days.
Service
AI automation of business processes
The estimate covers our team's work. Hardware, third-party service licences and travel are added on request.
Estimated cost
₽1M
Timeline
5 wk
Frequently asked questions
How do n8n and Make differ from a custom backend?
A low-code platform covers standard steps: a webhook, an API call, JSON parsing, a CRM write. n8n handles 3–5 processes up to 10,000 operations a day, while 100,000 events an hour and sub-second latency call for a custom backend.
How long does the launch take?
The pilot takes 3–4 weeks: audit, process map, three automations, and monitoring. The first scenario reaches real data within a week.
What happens on failure?
The node retries with a 30-second delay, writes the event to the log, and alerts the on-call engineer. After three retries the task goes to a person.
Which systems do you integrate?
We connect CRM, ERP, email, messengers, spreadsheets, and documents through APIs and webhooks. For systems without an API we use an export or a Kafka event bus.
What teams add to this service
Part of Solutions
Implementation Examples
×3
Publishing volume
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